Predictive system for context-aware custom web presentation

Web应用程序对于公司业务的发展至关重要。它是与现有和潜在客户共享信息的重要平台，也是重要的在线营销工具。该项目利用机器智能技术和工具为网站访问者定制网页演示，这将显著减少他们的搜索时间和挫折感。 访问者花在搜索相关内容上的时间对访问者和网站所有者来说都是至关重要的。搜索时间随着网络内容的增加而迅速增长，这给访问者带来了挫折感，并降低了他们的体验质量(QOE)。这种挫败感将客户从潜在的商机中赶走，转移到了网站所有者手中。因此，在Web呈现逻辑中构建智能以实时向用户呈现定制内容对于通过改善客户的冲浪体验来留住客户至关重要。在这个项目中，我们的目标是构建一个预测系统，用于对用户请求进行上下文感知处理，以实现定制的表示逻辑。 提出的定制Web展示系统包括用于处理Web请求的上下文配置文件和基于机器学习的预测算法以及用于识别定制内容的推荐系统。它将被实施，并与InnoHub平台集成。它将使InnoHub能够通过改善客户网站访问者的QOE来为客户提供业务增长。此外，它不仅将有助于增加加拿大的研发，还将通过推动更多客户进入收入流来促进其经济。

Web application is critical for the growth of a company's business. It is a significant platform for information sharing with existing and potential customers and an important online marketing tool. The project employs machine intelligence techniques and tools to customize web page presentation to the web-site visitors, which will significantly reduce their search time and frustration. The time a visitor spends on searching for relevant content is critical for both the visitors and the web site owners. The search time grows rapidly as the web content increases, which causes frustration to the visitors and drops their Quality of Experience (QoE). The frustration drives away customers from potential business opportunity to the web site owners. Hence, building intelligence in web presentation logic to present customized content to users within real time is critical for retaining customers by improving their surfing experience. In this project, we aim to build a predictive system for context-aware processing of user requests to implement customized presentation logic. The proposed customized web presentation system includes context profile for processing web requests and predictive algorithms based on machine learning and recommender system to identify the custom content. It will be implemented and integrated with innohub platform. It will enable innohub to offer business growth to its clients by improving the QoE of visitors to their web sites. Further, it will not only contribute to increase R&D in Canada but also to its economy by driving more customers into the revenue stream.